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Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency.

ABSTRACT: Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers.

SUBMITTER: Diaz BA

PROVIDER: S-EPMC4828461 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency.

Diaz B Alexander BA Hardstone Richard R Mansvelder Huibert D HD Van Someren Eus J W EJ Linkenkaer-Hansen Klaus K

Frontiers in psychology 20160412

Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance ...[more]

PMID: 27148107

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Project description:In this paper, we explore the utility of resting-state EEG measures as potential biomarkers for the detection and assessment of cognitive decline in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Neurophysiological biomarkers of AD derived from EEG and FDG-PET, once characterized and validated, would expand the set of existing diagnostic molecular biomarkers of AD pathology with associated biomarkers of disease progression and neural dysfunction. Since symptoms of AD often begin to appear later in life, successful identification of EEG-based biomarkers must account for age-related neurophysiological changes that occur even in healthy individuals. To this end, we collected EEG data from individuals with AD (n = 26), MCI (n = 53), and cognitively normal healthy controls stratified by age into three groups: 18-40 (n = 129), 40-60 (n = 62) and 60-90 (= 55) years old. For each participant, we computed power spectral density at each channel and spectral coherence between pairs of channels. Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). A smaller but significant increase in power of slow frequencies was observed for the MCI group, localized to temporal areas. These effects on slow frequency spectral power opposed that of normal aging observed by a decrease in the power of slow frequencies in our control groups. The AD group showed a significant decrease in the spectral power and coherence in the Alpha band consistent with the same effect in normal aging. However, the MCI group did not show any significant change in the Alpha band. Overall, Theta to Alpha ratio (TAR) provided the largest and most significant differences between the AD group and controls. However, differences in the MCI group remained small and localized. We proposed a novel method to quantify these small differences between Theta and Alpha bands' power using empirically derived distributions of spectral power across the time domain as opposed to averaging power across time. We defined Power Distribution Distance Measure (PDDM) as a distance measure between probability distribution functions (pdf) of Theta and Alpha power. Compared to average TAR, using PDDF enhanced the statistical significance, the effect size, and the spatial distribution of significant effects in the MCI group. We designed classifiers for differentiating individual MCI and AD participants from age-matched controls. The classification performance measured by the area under ROC curve after cross-validation were AUC = 0.85 and AUC = 0.6, for AD and MCI classifiers, respectively. Posterior probability of AD, TAR, and the proposed PDDM measure were all significantly correlated with MMSE score and neuropsychological tests in the AD group.

Project description:ObjectivePain is common among women with gynecologic cancer and contributes to depressed mood, sleep disturbances, and likelihood of future chronic pain. Little is known about how psychosocial factors are associated with central sensitization of pain in gynecologic cancer. This study examined relations among depressive symptoms, sleep, subjective pain, and aftersensation pain (a proxy for central sensitization of pain) in gynecologic cancer.MethodsParticipants were 42 women (mean age [SD] = 59.60 [10.11] years) enrolled in a randomized clinical trial examining psychological intervention effects on sleep, pain, mood, and stress hormones/cytokines in gynecologic cancer. Six to eight weeks after surgery, participants completed an assessment of depressive symptoms, sleep, and subjective pain and a temporal summation of pain protocol via quantitative sensory testing (QST).ResultsControlling for recent chemotherapy, history of chronic pain, and analgesic medication use, regression analyses revealed that longer sleep onset latency (SOL; B = 3.112, P = 0.039, bias-corrected and accelerated (BCa) 95% confidence interval [CI] = 0.371 to 6.014) and greater sensory pain (B = 0.695, P = 0.023, BCa 95% CI = 0.085 to 1.210) were associated with greater aftersensation pain at 15 seconds. Greater sensory pain scores were associated with greater aftersensation pain at 30 seconds (B = 0.286, P = 0.045, BCa 95% CI = 0.008 to 0.513). Depression was not associated with aftersensation pain. The overall models accounted for 44.5% and 40.4% of the variance in aftersensation pain at 15 and 30 seconds, respectively. Conclusions. Longer SOL and higher subjective sensory pain were related to greater aftersensation of experimentally induced pain in women postsurgery for gynecologic cancers. Interventions that improve sleep and subjective sensory pain during the perisurgical period may reduce risk for central sensitization of pain.

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Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency.

Publications

Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency.

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